Delineation of the trigeminal-lateral parabrachial-central amygdala tract in humans
Bibliographic record
Abstract
Abstract The parabrachial nucleus (PBN) relays interoceptive and exteroceptive information to limbic brain regions. In particular, lateral PBN projections to the central nucleus of the amygdala (CeA) are thought to encode the affective dimension of pain. Pain in the orofacial region is thought to be more unpleasant than pain elsewhere in the body because the face plays an important role in social interactions, feeding, and exploration. The trigeminal nerve (CN V) carries sensory, including nociceptive, information from the orofacial region to the central nervous system. Canonically, the affective dimension of orofacial pain is thought to be encoded by the medial trigeminothalamic tract, which projects to midline thalamic nuclei and further to limbic brain regions. A preclinical study identified an additional circuit that carries orofacial nociceptive information to subcortical limbic brain regions via the lateral PBN. This circuit, from the CN V to the lateral PBN and further to the CeA, is thought to contribute to the heightened negative affect of orofacial pain. However, the CN V–lateral PBN–CeA circuit has yet to be delineated in humans. Here, we aimed to resolve this circuit in humans with diffusion MRI from the Human Connectome Project (HCP) using probabilistic tractography. We first delineated the tract at 7T (n = 150) to determine whether this tract can be resolved. Next, we delineated the tract at the more readily available, but lower resolution 3T field strength (n = 155). Given the growing evidence of sex differences in pain mechanisms, as a secondary aim, we explored whether sex differences in connectivity strengths of the circuit existed in our sample. The basolateral amygdala (BLAT) was used as a negative control, as we did not anticipate CN V-lPBN-BLAT connectivity. The CN V–lPBN–CeA circuit had significantly stronger connectivity strength than the BLAT circuit at both field strengths (both p < 0.001). Only the right CN V–lPBN–CeA circuit at 3T showed significantly stronger connectivity in males than in females (p = 0.002). This study delineated the human CN V–lPBN–CeA circuit for the first time in vivo. This circuit may provide a neuroanatomical substrate for the heightened negative affect elicited by orofacial pain and could serve as a potential therapeutic target.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".